Processing support device, method and computer readable storage medium, and semiconductor fabrication support device and method

ABSTRACT

Using an equipment-classified processing results database, an intercept satisfying a second predetermined condition is derived from intercepts of straight lines that pass through a reference co-ordinate point, which satisfies a first predetermined condition, and respective co-ordinate points in a region bounded by: a line that passes through the reference co-ordinate point and is parallel to an x-axis representing wafer counts X; a y-axis representing processing durations Y; and a line passing through the reference co-ordinate point and the origin. Of co-ordinate points represented by an equipment and recipe-classified processing results database, a gradient satisfying a third predetermined condition is derived from gradients of lines that pass through the derived intercept and each of all co-ordinate points with wafer counts X at or above a predetermined number. A processing duration is derived using a regression equation into which the derived intercept and the derived gradient are substituted.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2011-076626 filed on Mar. 30, 2011, thedisclosure of which is incorporated by reference herein.

BACKGROUND

1. Technical Field

The present invention relates to a processing support device, method anda computer readable storage medium, and a semiconductor fabricationsupport device and method, and more specifically relates to a processingsupport device, method and a computer readable storage medium, and asemiconductor fabrication support device and method for a fabricationline that applies predetermined processing to targets with predeterminedequipment.

2. Related Art

Systems of equipment for applying predetermined processing to pluralnumbers of semiconductor wafers constituting individual lots (lotprocessing) fall into two categories. One category is batch systems thatsimultaneously process all the semiconductor wafers included in a lot atone time, and the other category is single-wafer systems that processthe semiconductor wafers included in a lot one at a time.

For a piece of equipment in any kind of system, a processing durationrequired for processing a lot may be ascertained by, for example,measuring a duration from when a start signal indicating that lotprocessing has started is inputted to when an end signal indicating thatthe lot processing has finished is inputted. A duration required for lotprocessing, a schedule of processing to be conducted before and afterthe lot processing, and suchlike may be administered using a durationthat is measured in this manner.

For example, Japanese Patent Application Laid-Open (JP-A) No. 6-291006discloses a technology with the object of improving fabricationperformance of a semiconductor fabrication line. This technologypredicts a completion duration of processing of a step on the basis ofprevious processing durations, and starts processing of a previous stepso as to be in time for the completion duration. However, JP-A No.6-291006 does not specifically disclose how a processing completionduration of a step is predicted on the basis of previous processingdurations. Consequently, specifying the processing start time of theprevious step is difficult in practice.

JP-A No. 2001-209421 discloses a technology with the object ofpredicting a completion duration of lot processing. This technologydefines processing durations of respective operations in accordance withstructures and operations of equipment and, through complexcalculations, predicts a duration of lot processing.

However, although the technology recited in JP-A No. 2001-209421 maypredict a completion duration of lot processing, extremely complicatedcalculations are required for predicting the processing duration.Therefore, if support is conducted using the processing recited in JP-ANo. 2001-209421 to perform lot processing in accordance with a scheduledduration, complicated calculations must be carried out.

Apart from cases of executing processing relating to semiconductors,similar problems also arise when, for example, the technology recited inJP-A No. 2001-209421 is used when some kind of processing is applied toprocessing targets other than semiconductors.

SUMMARY

The present invention has been made in order to solve the problemdescribed above, and an object of the invention is to provide aprocessing support device, method and a computer readable storagemedium, and a semiconductor fabrication support device and method thatare capable of simply and accurately supporting the application ofpredetermined processing to processing targets by predeterminedequipment in accordance with a scheduled duration.

A processing support device according to the first aspect of the presentinvention includes: a memory section that stores first two-dimensionalco-ordinate data that represents processing object unit counts X ofprocessing targets to which predetermined processing is applied bypredetermined equipment and processing durations Y required for theprocessing of the unit counts X of the processing targets as co-ordinatepoints in two dimensions, and second two-dimensional co-ordinate datathat represents unit counts X and processing durations Y for individualtypes of the processing as co-ordinate points in two dimensions; anintercept derivation section that derives an intercept b of a regressionequation expressed as the following expression (1)Y=aX+b  (1)in which the unit count X is an independent variable, the processingduration Y is a dependent variable, and b is an intercept and a is agradient particular to the equipment, the intercept b being an interceptthat satisfies a second condition among intercepts of lines that passthrough a reference co-ordinate point and respective co-ordinate pointsin a region, the reference co-ordinate point satisfying a firstpredetermined condition among the co-ordinate points represented by thefirst two-dimensional co-ordinate data stored in the memory section, andthe region being bounded by a line that passes through the referenceco-ordinate point and is parallel to an x-axis representing the unitcounts X, a y-axis representing the processing durations Y and a linethat passes through the reference co-ordinate point and the origin; agradient derivation section that derives the gradient a, the gradient abeing a gradient of a line that satisfies a third predeterminedcondition among gradients of lines that pass through the intercept bderived by the intercept derivation section and each of all co-ordinatepoints with a unit count X greater than or equal to a predeterminednumber among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data stored in the memory section; and asupport section that supports the processing using expression (1), intowhich the intercept b derived by the intercept derivation section andthe gradient a derived by the gradient derivation section aresubstituted.

According to the thirteenth aspect of the present invention, asemiconductor fabrication support device includes: a processing supportdevice according to any one of the first to the twelfth aspects; and aprediction section that predicts an end time of processing using thesupport section, wherein the processing targets are semiconductors.

According to the sixteenth aspect of the present invention a processingsupport method includes: registering, by storing in a memory section,first two-dimensional co-ordinate data that represents processing objectunit counts X of processing targets to which predetermined processing isapplied by predetermined equipment and processing durations Y requiredfor the processing of the unit counts X of the processing targets asco-ordinate points in two dimensions, and second two-dimensionalco-ordinate data that represents unit counts X and processing durationsY for individual types of the processing as co-ordinate points in twodimensions; deriving an intercept b of a regression equation expressedas the following expression (1)Y=aX+b  (1)in which the unit count X is an independent variable, the processingduration Y is a dependent variable, and b is an intercept and a is agradient particular to the equipment, the intercept b being an interceptthat satisfies a second condition among intercepts of lines that passthrough a reference co-ordinate point and respective co-ordinates in aregion, the reference co-ordinate point satisfying a first predeterminedcondition among the co-ordinate points represented by the firsttwo-dimensional co-ordinate data stored in the memory section, and theregion being bounded by a line that passes through the referenceco-ordinate point and is parallel to an x-axis representing the unitcounts X, a y-axis representing the processing durations Y and a linethat passes through the reference co-ordinate point and the origin;deriving the gradient a, the gradient a being a gradient of a line thatsatisfies a third predetermined condition among gradients of lines thatpass through the derived intercept b and each of all co-ordinate pointswith a unit count X greater than or equal to a predetermined numberamong the co-ordinate points represented by the second two-dimensionalco-ordinate data stored in the memory section; and supporting theprocessing using expression (1), into which the derived intercept b andthe derived gradient a are substituted.

According to the twenty-eighth aspect of the present invention, there isprovided a semiconductor fabrication support method including: aprocessing support method according to any one of the sixteenth to thetwenty-seventh aspects; and predicting an end time of processing, by thesupporting step, wherein the processing targets are semiconductors.

According to the thirty-first aspect of the present invention, there isprovided a non-transitory computer readable medium storing a programcausing a computer to execute a process for supporting processing, theprocess includes: registering, by storing in a memory section, firsttwo-dimensional co-ordinate data that represents processing object unitcounts X of processing targets to which predetermined processing isapplied by predetermined equipment and processing durations Y requiredfor the processing of the unit counts X of the processing targets asco-ordinate points in two dimensions, and second two-dimensionalco-ordinate data that represents unit counts X and processing durationsY for individual types of the processing as co-ordinate points in twodimensions; deriving an intercept b of a regression equation expressedas the following expression (1)Y=aX+b  (1)in which the unit count X is an independent variable, the processingduration Y is a dependent variable, and b is an intercept and a is agradient particular to the equipment, the intercept b being an interceptthat satisfies a second condition among intercepts of lines that passthrough a reference co-ordinate point and respective co-ordinates in aregion, the reference co-ordinate point satisfying a first predeterminedcondition among the co-ordinate points represented by the firsttwo-dimensional co-ordinate data stored in the memory section, and theregion being bounded by a line that passes through the referenceco-ordinate point and is parallel to an x-axis representing the unitcounts X, a y-axis representing the processing durations Y and a linethat passes through the reference co-ordinate point and the origin;deriving the gradient a, the gradient a being a gradient of a line thatsatisfies a third predetermined condition among gradients of lines thatpass through the derived intercept b and each of all co-ordinate pointswith a unit count X greater than or equal to a predetermined numberamong the co-ordinate points represented by the second two-dimensionalco-ordinate data stored in the memory section; and supporting theprocessing using expression (1), into which the derived intercept b andthe derived gradient a are substituted.

According to the present invention, an advantageous effect is providedin that the application of predetermined processing to processingtargets by predetermined equipment in accordance with a scheduledduration may be simply and accurately supported.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present invention will be described indetail based on the following figures, wherein:

FIG. 1 is a block diagram illustrating an example of structure of afabrication processing device relating to an exemplary embodiment.

FIG. 2 is a schematic diagram illustrating principal memory contents ofa hard disc of the fabrication processing device relating to theexemplary embodiment.

FIG. 3 is a schematic diagram illustrating principal memory contents ofa processing results database relating to the exemplary embodiment.

FIG. 4 is a distribution plot representing principal memory contents ofan equipment-classified processing results database relating to theexemplary embodiment as two-dimensional co-ordinates.

FIG. 5 is a distribution plot representing principal memory contents ofan equipment and recipe-classified processing results database relatingto the exemplary embodiment as two-dimensional co-ordinates.

FIG. 6 is a flowchart illustrating the flow of processing of aprocessing results registration program relating to the exemplaryembodiment.

FIG. 7 is a schematic diagram illustrating an example of a processingresults registration screen relating to the exemplary embodiment.

FIG. 8 is a flowchart illustrating the flow of processing of aprocessing duration prediction routine program relating to the exemplaryembodiment.

FIG. 9 is a schematic diagram illustrating an example of a predictioncondition input screen relating to the exemplary embodiment.

FIG. 10 is a flowchart illustrating the flow of processing of anintercept derivation routine program relating to the exemplaryembodiment.

FIG. 11 is a graph illustrating a correlation between processingdurations calculated from processing start data and processing end data,which are inputted by an administrator in order to construct theprocessing results database relating to the exemplary embodiment, andcounts of such inputs.

FIG. 12 is a flowchart illustrating the flow of processing of a gradientderivation routine program relating to the exemplary embodiment.

FIG. 13 is a (first) schematic diagram illustrating an example of adisplay state of a display of the fabrication processing device relatingto the exemplary embodiment.

FIG. 14 is a (second) schematic diagram illustrating an example of adisplay state of the display of the fabrication processing devicerelating to the exemplary embodiment.

FIG. 15 is a (third) schematic diagram illustrating an example of adisplay state of the display of the fabrication processing devicerelating to the exemplary embodiment.

FIG. 16 is a (fourth) schematic diagram illustrating an example of adisplay state of the display of the fabrication processing devicerelating to the exemplary embodiment.

DETAILED DESCRIPTION

Herebelow, an example of a mode for embodying the present invention isdescribed in detail with reference to the attached drawings. In thepresent exemplary embodiment, an example of a mode in which fabricationof semiconductor wafers by a fabrication line, which includes a numberof processing steps, is supported is described. Pieces of equipment thatcarry out the corresponding processing one machine after another in theprocessing steps are provided on the fabrication line.

FIG. 1 is a block diagram illustrating an example of principalstructures of an electronic system of a fabrication support device 10relating to the present exemplary embodiment. The fabrication supportdevice 10 relating to the present exemplary embodiment supports thefabrication of semiconductor wafers at a fabrication line by predictingdurations required for processing carried out by each of the pluralpieces of equipment that constitute the fabrication line (which are, forexample, conveyance robots, grinding machines and the like), anddisplaying the prediction results. The fabrication support device 10 isequipped with a central processing unit (CPU) 10A, a random accessmemory (RAM) 10B, a read-only memory (ROM) 10C, a hard disc 10D, aninput device 10E, a display 10F and an input/output port 10G. The CPU10A oversees overall operations of the fabrication support device 10.The RAM 10B is used as a work area during execution of variousprocessing programs by the CPU 10A, and the like. Various processingprograms and various parameters and the like are pre-stored in the ROM10C. The hard disc 10D is used for storing various kinds of data. Theinput device 10E includes a keyboard and mouse or the like to be usedfor inputting various kinds of data. The display 10F is used fordisplaying various kinds of data. The input/output port 10G exchangesvarious kinds of data with an external device 11 (for example, apersonal computer) through a communications unit (for example, a localarea network (LAN)). These components are connected to one another by abus 12.

Thus, the CPU 10A may access the RAM 10B, the ROM 10C and the hard disc10D, acquire various kinds of input data via the input device 10E,display various kinds of data at the display 10F and, via theinput/output port 10G, exchange various kinds of data with the externaldevice 11 connected to the communications unit.

FIG. 2 schematically illustrates principal memory contents of the harddisc 10D.

As illustrated in FIG. 2, the hard disc 10D is provided with a databasearea DB, which is for storing various databases, and a program area PG,which is for storing a control program for controlling the fabricationsupport device 10, various programs for carrying out various kinds ofprocessing, and the like.

The database area DB includes a processing results database DB1,representing results of processing by the fabrication line (processingresults), an equipment-classified processing results database DB2representing processing results for individual pieces of equipment, andan equipment and recipe-classified processing results database DB3representing processing results for individual recipes at each piece ofequipment.

Herebelow, structures of these databases are described in detail withreference to the drawings.

As illustrated in FIG. 3, the processing results database DB1 relatingto the present exemplary embodiment is constituted by the following databeing associated with one another and stored in the database area DB:processing start data representing a date and time at which processingby specific equipment started according to the judgment of anadministrator; processing end data representing the date and time atwhich the processing by the specific equipment ended according to thejudgment of an administrator; equipment name data representing thespecific piece of equipment; wafer count data indicating the number ofsemiconductor wafers (the number of individual units) constituting asingle lot; recipe data representing a recipe associated with theprocessing by the specific equipment (conditions determined by thefabricated product and steps); and processing duration data which is theduration required for the processing by the specific equipment. In thedescriptions below, the data stored in the processing results databaseDB1—that is, the processing start data, processing end data, equipmentname data, wafer count data, recipe data and processing duration—arereferred to as processing results data where there is no need todistinguish therebetween.

The equipment-classified processing results database DB2 relating to thepresent exemplary embodiment is constructed by two-dimensionalco-ordinates being stored in the database area for each type ofequipment name data. With the wafer count data and processing durationsthat are stored in the processing results database DB1 as objects, thewafer counts represented by the wafer count data are represented by xco-ordinates and the processing durations corresponding to the wafercount data records are represented by y co-ordinates. FIG. 4 shows anexample of a distribution plot illustrating a distribution oftwo-dimensional co-ordinates stored in the equipment-classifiedprocessing results database DB2.

The equipment and recipe-classified processing results database DB3relating to the present exemplary embodiment is constructed bytwo-dimensional co-ordinates being stored in the database area DB foreach type of equipment name data and each type of recipe data. With thewafer counts represented by the wafer count data and processingdurations stored in the processing results database DB1 as objects, thewafer count data is represented by x co-ordinates and the processingdurations corresponding to the wafer count data records are representedby y co-ordinates. FIG. 5 shows an example of a distribution plotillustrating a distribution of two-dimensional co-ordinates stored inthe equipment and recipe-classified processing results database DB3.

Now, operation of the fabrication support device 10 relating to thepresent exemplary embodiment is described.

Firstly, operation of the fabrication support device 10 when processingresults data is being registered by a fabrication line administrator isdescribed with reference to FIG. 6. FIG. 6 is a flowchart illustratingthe flow of processing of a processing results data registration programthat is executed by the CPU 10A of the fabrication support device 10when an instruction to register processing results data is given to thefabrication support device 10 by the administrator. This program isstored in advance in the program area PG of the hard disc 10D.

In step 100 of FIG. 6, the administrator inputs data with the inputdevice 10E to cause the display of a processing results dataregistration screen. Accordingly, the CPU 10A displays the processingresults data registration screen at the display 10F and, in step 102,waits for the input of predetermined data through the input device 10E.

FIG. 7 illustrates an example of the processing results dataregistration screen that is displayed at the display 10F. As illustratedin FIG. 7, in the processing results data registration screen relatingto the present exemplary embodiment, a message prompting the input ofprocessing results data is displayed, and names of items that can beregistered are displayed along with rectangular boxes for inputting theprocessing results data corresponding to those items.

When the processing results data registration screen is displayed at thedisplay 1 OF as illustrated in FIG. 7, the administrator inputsprocessing results data in the boxes corresponding to the fields intowhich processing results data should be inputted, with the input device10E. When the input is complete, the administrator selects an “End”button displayed at the bottom of the processing results dataregistration screen with the mouse (pointing device) included in theinput device 10E or the like. The administrator must input processingresults data of any items belonging to required fields. The itemsbelonging to required fields in the example in FIG. 7 are the processingstart data, the processing end data, the equipment name data, the wafercount data and the recipe data. The processing duration is calculated bythe CPU 10A when input of both the processing start data and theprocessing end data is complete, and is entered into the box of thecorresponding item. FIG. 7 illustrates an example in which 1 hour, 9minutes (1:09) is entered.

When the “End” button is selected by the administrator, the result ofthe judgment in step 102 is positive and the CPU 10A proceeds to step104.

In step 104, the CPU 10A associates the processing start data,processing end data, equipment name data, wafer count data, recipe dataand processing duration that have been inputted into the processingresults data registration screen by the administrator with one anotherand registers these in the hard disc 10D. Thus, the processing resultsdatabase DB1 is constructed by the inputted processing start data,processing end data, equipment name data, wafer count data, recipe dataand processing duration at the processing results data registrationscreen by the administrator being mutually associated and stored in thedatabase area DB. When the processing of step 104 is finished, the CPU10A ends the present processing results data registration program.

The processing results database DB1 illustrated in FIG. 3 isprogressively constructed by execution of the above-described processingresults data registration program.

Now, operation of the fabrication support device 10 when execution ofprocessing duration prediction processing that predicts a duration ofprocessing by specific equipment is required is described with referenceto FIG. 8. FIG. 8 is a flowchart illustrating the flow of processing ofa processing duration prediction program that is executed by the CPU 10Aof the fabrication support device 10 when an instruction to execute theprocessing duration prediction is given to the fabrication supportdevice 10 by an administrator. This program is stored in advance in theprogram area PG of the hard disc 10D.

In step 150 of FIG. 8, the administrator inputs data with the inputdevice 10E to cause the display of a prediction conditions input screen.Accordingly, the CPU 10A displays the prediction conditions input screenat the display 10F and, in step 152, waits for the input ofpredetermined data through the input device 10E.

FIG. 9 illustrates an example of the prediction conditions input screenthat is displayed at the display 10F. As illustrated in FIG. 9, in theprediction conditions input screen relating to the present exemplaryembodiment, a message prompting the input of conditions for predictingthe processing duration (processing conditions) is displayed, and namesof items that can be inputted are displayed along with rectangular boxesfor inputting the prediction conditions corresponding to those items.

When the prediction conditions input screen is displayed at the display10F as illustrated in FIG. 9, the administrator inputs the predictionconditions in the boxes corresponding to the fields into whichprocessing results data should be inputted with the input device 10E.When the input is complete, the administrator selects an “End” buttondisplayed at the bottom of the prediction conditions input screen withthe mouse (pointing device) included in the input device 10E or thelike. The administrator must input prediction conditions of any itemsbelonging to required fields. The items belonging to required fields inthe example in FIG. 9 are the equipment name data, the wafer count dataand the recipe data.

When the “End” button is selected by the administrator, the result ofthe judgment in step 152 is positive and the CPU I OA proceeds to step154. In step 154, the CPU 10A reads the wafer count data and processingdurations corresponding to the equipment name data inputted by theprocessing of step 152 from the processing results database DB1. The CPU10A registers two-dimensional co-ordinates according to the wafer countdata and processing durations that have been read out in the hard disc10D. The CPU 10A also reads wafer count data and processing durationsthat correspond to both the equipment name data and the recipe datainputted by the processing of step 152 from the processing resultsdatabase DB1, and registers two-dimensional co-ordinates according tothese wafer count data and processing durations in the hard disc 10D. Inother words, the CPU 10A constructs the equipment-classified processingresults database DB2 by reading out the wafer count data and processingdurations that correspond to the equipment name data inputted by theprocessing of step 152 from the processing results database DB1 andstoring two-dimensional co-ordinates according to the read out wafercount data and processing durations in the database area DB for theindividual type of equipment name data. In addition, the CPU 10Aconstructs the equipment and recipe-classified processing resultsdatabase DB3 by reading out the wafer count data and processingdurations that correspond to both the equipment name data and the recipedata inputted by the processing of step 152 from the processing resultsdatabase DB1 and storing two-dimensional co-ordinates according to theread out wafer count data and processing durations in the database areaDB for the individual combination of equipment name data and recipedata.

When the processing of step 154 is complete, the CPU 10A proceeds tostep 156 and executes an intercept derivation routine program asfollows, on the basis of the equipment-classified processing resultsdatabase DB2.

FIG. 10 is a flowchart illustrating the flow of processing of theintercept derivation routine program. In step 200 of FIG. 10, the CPU10A displays the two-dimensional co-ordinates stored in theequipment-classified processing results database DB2 at the display 10Fin the form of, for example, a distribution plot as illustrated in FIG.4. The lines b, d and e shown in FIG. 4 are not displayed on the display10F at this time. In the example of FIG. 4, the numbers of semiconductorwafers represented by the wafer count data are shown on the horizontalaxis (hereinafter referred to as the x-axis), and the processingdurations are shown on the vertical axis (hereinafter referred to as they-axis). Herebelow, where appropriate for description, a number ofsemiconductor wafers represented by the wafer count data is referred toas a wafer count X, and a processing duration is referred to as aprocessing duration Y.

Then, in step 202, the CPU 10A extracts co-ordinate points that satisfya first predetermined condition from the respective points (co-ordinatepoints) of the two-dimensional co-ordinates represented by thedistribution plot that is currently being displayed at the display 10F.The CPU 10A then highlights the extracted co-ordinate points in thedisplay 10F by changing them to a display condition (for example, aninverted display condition) that may distinguish them from the rest ofthe co-ordinate points as being candidates for a reference co-ordinatepoint.

In the processing of step 202 in the present exemplary embodiment, thefirst predetermined condition is the conditions that a co-ordinate pointhas a maximum value of the wafer counts X and that the processingduration Y falls in a first duration band. Here, the meaning of the term“first duration band” refers to a band of the processing durations ofthe co-ordinate points being displayed in the distribution plot at thedisplay 10F by the processing of step 200 whose wafer counts X are themaximum value (in the example in FIG. 4, the wafer count X=50). Thefirst duration band is a band of processing durations of co-ordinatepoints among these co-ordinate points whose positions, counting from aminimum processing duration, are proportions, relative to the totalnumber of co-ordinate points whose wafer counts X are the maximum value(hereinafter referred to as first proportions), of from 5% to 35%. Inthe fabrication support device 10, to enable a more accurate predictionof a processing duration, it is preferable if the first proportions arefrom 10% to 20%. For example, in the distribution plot illustrated inFIG. 4, the number of co-ordinates corresponding to wafer count X=50 is100. Therefore, among the co-ordinate points with wafer count X=50 inthis case, a duration band of the processing durations Y of theco-ordinate points from a minimum value at 10% counting from the minimumprocessing duration Y (i.e., the 10th co-ordinate point) to a maximumvalue at 20% (i.e., the 20th co-ordinate point) may be employed as thefirst duration band.

FIG. 11 is a graph illustrating a correlation between the processingdurations Y calculated from the processing start data and processing enddata that have been inputted for constructing the processing resultsdatabase DB1 (the horizontal axis in the example in FIG. 11) and thenumber of times individual inputs in which the processing start data andprocessing end data required for calculating a particular processingduration have been inputted by administrators (the vertical axis in theexample in FIG. 11). As illustrated in FIG. 11, many unusual datapoints, due to input errors and the like, are present in the vicinity ofa minimum value of the processing duration Y (the vicinity of theorigin) and the vicinity of a maximum value. Accordingly, on a practicallevel, the present inventors have previously observed as a result ofdiligent investigations based on empirical rules that it is preferableif the proportions relative to the total number of co-ordinate pointsare from 5% to 35% (from 0.4 hours to 0.6 hours in the example in FIG.11). If a processing duration Y included at a co-ordinate point shouldbe employed as an ultimate forecast result with a higher level ofreliability, the present inventors have previously observed as a resultof diligent investigations based on empirical rules that it ispreferable if the proportions relative to the total number ofco-ordinate points are from 10% to 20% (in the example in FIG. 11, theprocessing duration Y at which the number of inputs is at the maximumand processing durations Y in the vicinity thereof).

Then, in step 204, the administrator uses the input device 10E (forexample, the mouse) to designate one of the reference co-ordinate pointcandidates highlighted in the display 10F by the processing of step 202.In the example shown in FIG. 4, the co-ordinate points that are thereference co-ordinate point candidates are displayed in a cluster in thedisplay 10F. Accordingly, in the present exemplary embodiment, byoperating the keyboard and/or mouse included at the input device 10E,the administrator can easily instruct that a predetermined regioncontaining the co-ordinate points currently highlighted in the display10F should be displayed magnified. In the example shown in FIG. 4, theco-ordinate point “c” is designated as the reference co-ordinate point.The highlighted display state of co-ordinate points other than thedesignated reference co-ordinate point c is cancelled.

When the administrator designates the reference co-ordinate point c bythe processing of step 204, the result of the judgment is positive andthe CPU 10A proceeds to step 206. In step 206, the CPU 10A extractsintercepts that satisfy a second predetermined condition from interceptsof lines (straight lines, as are other lines mentioned hereinafter) thatpass through the reference co-ordinate point c designated by theprocessing of step 204 and co-ordinate points that, as illustrated bythe example in FIG. 4, are in a region bounded by: a line “e” thatpasses through the reference co-ordinate point c and is parallel to thex-axis; the y-axis; and a line “d” that passes through the referenceco-ordinate point c and the origin. The CPU 10A then highlightsco-ordinate points corresponding to the extracted segment in the display10F as intercept candidates, by switching these co-ordinate points to adisplay state that may be distinguished from the rest of the co-ordinatepoints (for example, a display state with a color different from thecolor of the other co-ordinate points).

In the processing of step 206 in the present exemplary embodiment, thesecond predetermined condition is a condition that, counting theintercept candidate co-ordinate points highlighted in the display 10Ffrom a minimum value, the positions of intercept candidate co-ordinatepoints are proportions, relative to the total number of intercepts ofthe lines passing through the reference co-ordinate point c and therespective co-ordinate points in the region bounded by line e, they-axis and line d (referred to hereinafter as second proportions), in arange from 5% to 35%. The present inventors have previously observed asa result of diligent investigations based on empirical rules thatemploying the range from 5% to 35% counting from the minimum value asthe second proportions is excellent. The present inventors have alsopreviously observed as a result of diligent investigations based onempirical rules that it is preferable if the second proportions are from10% to 20%.

Then, in step 208, the administrator uses the input device 10E (forexample, the mouse) to designate one of the intercept candidateco-ordinate points highlighted in the display 10F by the processing ofstep 206. In the example shown in FIG. 4, the co-ordinate points thatare intercept candidates are displayed in a cluster in the display 10F.Accordingly, in the present exemplary embodiment, by operating thekeyboard and/or mouse included at the input device 10E, theadministrator can easily instruct that a predetermined region containingthe co-ordinate points currently highlighted in the display 10F shouldbe displayed magnified. In the example shown in FIG. 4, the co-ordinatepoint “b” is designated as an intercept co-ordinate point to beultimately used, and the highlighted display state of the otherco-ordinate points is cancelled.

When the administrator designates the co-ordinate point b by theprocessing of step 208, the result of the judgment is positive and theCPU 10A proceeds to step 210. In step 210, the CPU 10A stores theco-ordinate point b designated by the processing of step 208 in apredetermined memory area of the hard disc 10D as a fixed value for theequipment represented by the equipment name data that has been inputtedas a prediction condition. Then the CPU 10A ends the present interceptderivation routine program and proceeds to step 158 shown in FIG. 8.

In step 158, the CPU 10A executes a gradient derivation routine programas follows, based on the equipment and recipe-classified processingresults database DB3.

FIG. 12 is a flowchart illustrating the flow of processing of thegradient derivation routine program. In step 250 of FIG. 12, the CPU 10Adisplays the two-dimensional co-ordinates stored in the equipment andrecipe-classified processing results database DB3 at the display 10F inthe form of, for example, a distribution plot as illustrated in FIG. 5.The linear graph shown in FIG. 5 is not displayed at the display 10F atthis time. In the example of FIG. 4, the same as in FIG. 4, the wafercount X is shown on the horizontal axis (the x-axis) and the processingduration Y is shown on the vertical axis (the y-axis).

Then, in step 252, the CPU 10A determines whether or not the totalnumber of co-ordinate points present in the distribution plot displayedat the display 10F is 1,000 or more. If the result of the judgment ispositive, the CPU 10A proceeds to step 254, derives mathematicalexpressions, and then proceeds to step 256. The expressions (first-orderrelationships based on the wafer count X and the predetermined durationY) represent straight lines passing through the intercept b stored inthe predetermined memory area of the hard disc 10D by the processing ofstep 156 and each of co-ordinate points in the top 10%, counting fromhigher wafer counts X, of the total number of co-ordinate points in thedistribution plot displayed at the display 10F.

On the other hand, if the result of the judgment of step 252 isnegative, the CPU 10A proceeds to step 258 and determines whether or notthe total number of co-ordinate points present in the distribution plotdisplayed at the display 10F is 10 or less. If the result of thejudgment in step 258 is positive, the CPU 10A proceeds to step 260,derives mathematical expressions, and then proceeds to step 256. Theexpressions (first-order relationships based on the wafer count X andthe predetermined duration Y) represent straight lines passing throughthe co-ordinate point (intercept) b stored in the predetermined memoryarea of the hard disc 10D by the processing of step 156 and each of allthe co-ordinate points in the distribution plot displayed at the display10F.

On the other hand, if the result of the judgment of step 258 isnegative, the CPU 10A proceeds to step 262, derives mathematicalexpressions, and then proceeds to step 256. The expressions (first-orderrelationships based on the wafer count X and the predetermined durationY) represent straight lines passing through the co-ordinate point(intercept) b stored in the predetermined memory area of the hard disc10D by the processing of step 156 and each of co-ordinate points in thetop 50%, counting from higher wafer counts X, of the total number ofco-ordinate points in the distribution plot displayed at the display10F. In the example shown in FIG. 5, the co-ordinate points contained inthe region “f” show the co-ordinate points in the top 50%, counting fromhigh wafer counts X, of the total number of co-ordinate points presentin the distribution plot displayed at the display 10F.

In step 256, the CPU 10A displays at the display 10F, of the linesrepresented by the mathematical expressions derived by the processing ofstep 254, step 260 or step 262, lines other than lines with a gradientof less than zero. In addition, the CPU 10A highlights in the display10F, of the display object lines, lines with a gradient that satisfies athird predetermined condition, such that these lines may bedistinguished from other lines. The third predetermined condition instep 256 is a condition that, of the gradients of all the linesdisplayed in accordance with the expressions derived by the processingof step 254, step 260 or step 262, gradients are in a range from 10% to40% counting from the smallest gradient. The present inventors havepreviously observed as a result of diligent investigations based onempirical rules that employing the range 10% to 40% counting from thesmallest value of gradients among all the lines is excellent. Thepresent inventors have also previously observed as a result of diligentinvestigations based on empirical rules that it is preferable if thethird condition is that, among the gradients of all the lines displayedin accordance with the expressions derived by the processing of step254, step 260 or step 262, gradients are in a range from 10% to 20%counting from the smallest gradients.

Then, in step 264, the administrator uses the input device 10E (forexample, the mouse) to designate one of the lines highlighted in thedisplay 10F by the processing of step 256. In the present exemplaryembodiment, the administrator can easily instruct with the mouse that apredetermined region containing the lines currently highlighted in thedisplay 10F should be displayed magnified. In the example shown in FIG.5, a line with the gradient (coefficient) “a” is designated as a line tobe ultimately used for predicting a processing duration Y.

When a line is designated by the processing of step 264, the result ofthe judgment is positive, the CPU 10A proceeds to step 266, and thegradient a of the line designated by the processing of step 264 isstored in a predetermined memory area of the hard disc 10D. Then the CPU10A ends the present gradient derivation routine program and proceeds tostep 160 shown in FIG. 8.

In step 160, the CPU 10A calculates a processing duration using the linederived by the processing of step 264. That is, the CPU 10A calculatesthe processing duration by substituting a wafer count X represented bythe wafer count data that was inputted by the processing of step 152into a mathematical expression (1). Expression (1) is a regressionequation in which the wafer count X is an independent variable and thepredetermined duration Y is a dependent variable. The expression (1)includes the gradient a stored in the predetermined memory area of thehard disc 10D by the processing of step 266, and uses the co-ordinatepoint b stored in the predetermined memory area of the hard disc 10D bythe processing of step 210 as an intercept. In the present exemplaryembodiment, “a” in expression (1) is a coefficient correspondingapproximately to a processing duration for one wafer, and “b” is a valueparticular to each piece of equipment and represents a particularduration required for processing a lot (for example, a wafer alignmentduration required for processing of the first wafer in a lot, a durationrequired for vacuum suction, a preparatory task duration that occursregardless of a number of wafers to be processed, and the like).Y=aX+b  (1)

Then, in step 162, the CPU 10A displays the processing duration Yobtained from the calculation by the processing of step 160 at thedisplay 10F. For example, as illustrated in FIG. 13, the CPU 10Adisplays on the display 10F that the duration forecast as a processingduration for one lot (a processing scheduled duration) is 2 hours, 56minutes (2:56). After the processing scheduled duration is displayed atthe display 10F in this manner, the CPU 10A ends the present processingduration prediction program. Thus, in the fabrication support device 10relating to the present exemplary embodiment, a processing duration maybe easily and accurately predicted by executing the processing durationprediction program.

As is described in detail hereabove, according to the fabricationsupport device 10 relating to the present exemplary embodiment, theequipment-classified processing results database DB2, in which wafercounts X for individual lots of semiconductors to which predeterminedprocessing is applied by a predetermined piece of equipment andprocessing durations Y required for processing the wafer counts X arerepresented by co-ordinate points in two dimensions, and the equipmentand recipe-classified processing results database DB3, in which wafercounts X in individual recipes at each piece of equipment and processingdurations Y required for processing of the wafer counts X arerepresented by co-ordinate points in two dimensions, are stored in thehard disc 10D. An intercept b of a regression equation is derived, whichregression equation is represented by expression (1) in which the wafercount X is the independent variable, the processing duration Y is thedependent variable, and b is the intercept and a the gradient particularto the piece of equipment. That is, of the co-ordinate pointsrepresented by the equipment-classified processing results database DB2,an intercept b that satisfies the second predetermined condition isderived from among intercepts of straight lines that pass through areference co-ordinate point c that satisfies the first predeterminedcondition and respective co-ordinate points in a region which is boundedby: a line e that passes through the reference co-ordinate point c andis parallel to the x-axis representing wafer counts X; the y-axisrepresenting processing durations Y; and a line d that passes throughthe reference co-ordinate point c and the origin. Then, as the gradienta, among the co-ordinate points represented by the equipment andrecipe-classified processing results database DB3, the gradient of aline that satisfies the third predetermined condition is derived fromamong gradients of lines that pass through the intercept b and each ofall the co-ordinate points that have wafer counts X of at least apredetermined number. Then, the derived intercept b and gradient a aresubstituted into expression (1), which is used to calculate a processingduration Y, and processing at the predetermined piece of equipment issupported. Thus, applying processing to processing targets with apredetermined piece of equipment in accordance with a scheduled durationmay be simply and accurately supported.

Therefore, an operator may be reliably placed at a predetermined workposition at a lot processing end time, and wasted time at a fabricationline due to waiting for a person may be kept to a minimum. According totests by the present inventors, person-waiting time has been in theregion of 5% to 20% with the related art. In contrast, we have alreadyseen that when the present invention is employed, an improvement ofaround 5% in availability (and sales) may be expected. Furthermore,because operators may be efficiently positioned to meet end times, aneffect of reducing man-hours may be expected.

Problems and the like in conveyance systems, process systems and thelike may be detected for respective lot processes from the calculatedprocessing durations Y. Furthermore, by SPC management of fine timingvariations based on the processing durations Y, problems may be quicklydetected and the spread of trouble may be prevented.

In the exemplary embodiment described above, an example is described inwhich a co-ordinate point and a line displayed at the display 10F aredesignated by the administrator through the input device 10E. However,rather than being designated by an administrator, a single co-ordinatepoint and a single line may be extracted and used by the CPU 10A inaccordance with predetermined algorithms. For example, an example may begiven in which, if there are plural co-ordinate points included in thefirst duration band described above, a single co-ordinate point that isobtained by a predetermined algorithm from these co-ordinate points (forexample, random extraction) is used. Further, there is an example inwhich a single line that is obtained by a predetermined algorithm (forexample, random extraction) from the lines highlighted in the display10F in the processing of the above-described step 256 is used.

In the exemplary embodiment described above, an example in whichprocessing durations are calculated and the processing results databaseDB I is constructed on the basis of data provided by manual input by anadministrator, in which large errors are likely to occur, is described.However, when constructing the processing results database DB1,processing durations may be calculated using time data that is reportedby computer processing from a piece of equipment. Alternatively, aprocessing start signal representing a start of processing and aprocessing end signal representing the end of processing may berespectively received and a processing duration calculated from thereception interval. Further, both processing durations that arecalculated from data provided by manual input by an administrator andprocessing durations that are calculated from data reported byprocessing by computers from equipment may be used for construction ofthe processing results database DB1. The present invention may moderatea reduction in reliability of scheduled processing durations that arecalculated using a processing results database DB1 constructed on thebasis of data obtained by manual input by an administrator. Therefore,the present invention is more likely to provide a large effect than whenscheduled processing durations are calculated using a processing resultsdatabase DB1 constructed on the basis of data reported by the processingof computers.

In the above exemplary embodiment, an example is described in which thescheduled processing duration is displayed at the display 10F. However,this is not limiting. A scheduled processing duration may be audiblyexpressed by a voice reproduction device. A scheduled processingduration may also be presented to be permanently visible by a printer.Furthermore, combinations of visual display by the display 10F, audibleexpression by a voice reproduction device and permanently visibledisplay by a printer are possible.

In the above exemplary embodiment, administrators compare scheduledprocessing durations displayed at the display 10F with ideal processingdurations and make changes to recipes, changes to numbers ofsemiconductor wafers to be fabricated and the like. However, an idealprocessing duration may be inputted to the fabrication support device 10in advance and, for example, a warning may be given through the display10F if a difference between a calculated scheduled processing durationand the ideal processing duration is more than a predetermined duration.A means for giving the warning is not limited to the display 10F but maybe another output device such as a voice reproduction device or aprinter or the like.

In the above exemplary embodiment, an example is described ofcalculating a scheduled duration required for processing semiconductorwafers. However, this is not limiting. For example, after processingbegins, a time at which the silicon wafers are conveyed by a conveyancedevice such as a conveyor belt or the like and arrive at a predeterminedposition (a scheduled arrival time) may be calculated. For example, anexample may be given in which a time that is obtained by adding ascheduled processing duration calculated by the processing of step 160to a processing start time represented by the processing start datainputted as illustrated in FIG. 7 is employed as a scheduled arrivaltime. As illustrated by the example in FIG. 14, an administrator mayeasily ascertain the scheduled arrival time by the scheduled arrivaltime calculated in this manner being displayed at the display 10F. Thus,spare time going to waste in a fabrication line may be minimized andavailability may be improved by optimizing batch processing (decidingwhether to wait for lots to meet up and form a batch or to carry outprocessing without waiting), for example, in a diffusion furnace.Furthermore, lot processing may be held up by periodic maintenance of afabrication line, which may lead to great delays, particularly of urgentlot processing and the like. However, because arrival times may beaccurately predicted, flexibility in maintenance operation plans may beimproved and time losses moderated.

The performance of a piece of equipment represented by equipment namedata inputted to the fabrication support device 10 may be evaluated onthe basis of a scheduled processing duration calculated by executing theprocessing duration prediction program. For example, there may be anexample in which the extent to which a scheduled processing duration isslower than a processing duration actually measured at evaluationreference equipment is evaluated into multiple levels. This scheduledprocessing duration is calculated by inputting wafer count data andrecipe data representing respective wafer counts and recipes that havebeen actually been processed by the evaluation reference equipment intothe fabrication support device 10 and executing the processing durationprediction program. The meaning of the term “evaluated into multiplelevels” as used herein includes, for example, evaluating a case in whichthere is no slowing in the scheduled processing duration calculated bythe fabrication support device 10 relative to a processing durationactually measured at the evaluation reference equipment as being at rankA, evaluating a case in which there is a slowing of less than a minutein the scheduled processing duration calculated by the fabricationsupport device 10 relative to the processing duration actually measuredat the evaluation reference equipment as being at rank B, and evaluatinga case in which there is a slowing of more than a minute in thescheduled processing duration calculated by the fabrication supportdevice 10 relative to the processing duration actually measured at theevaluation reference equipment as being at rank C. An evaluation resultmay be displayed at the display 10F, for example, as illustrated in FIG.15. Thus, the risks of judging that processing is possible when it isnot (missing deadlines and reducing sales) and, conversely, the risks ofjudging that processing is not possible when it is (lost orders andover-investment) may be avoided.

Using equipment represented by equipment name data inputted to thefabrication support device 10 as an evaluation target, relative to atotal number of times the scheduled processing duration is calculated, aproportion of times that the processing scheduled direction and theactually measured processing duration match to within a predeterminederror may be calculated, and this proportion may be displayed at thedisplay 10F, as in the example illustrated in FIG. 16, as a degree ofreliability of the scheduled processing durations. The above-describedverification of equipment performance and verification of scheduledprocessing duration reliability may be carried out on the sameequipment.

In the above exemplary embodiment, the method of derivation of themathematical expression representing a straight line may be altered inaccordance with the total number of co-ordinate points by the executionof the gradient derivation program. However, this is not limiting.Mathematical expressions (first-order relationships based on the wafercount X and the predetermined duration Y) that represent lines passingthrough the co-ordinate point b and each of the co-ordinate points inthe top 50% of the total number of co-ordinate points counting from highwafer counts X may be derived regardless of the total number ofco-ordinate points. Using the top 50% means that lines with highaccuracy are drawn from data with high numbers of wafers. The presentinventors have previously observed as a result of diligentinvestigations based on empirical rules that the top 50% will almostalways be sufficient for obtaining accuracy.

In the above exemplary embodiment, an example is described of supportingfabrication of semiconductor wafers by substituting a wafer number Xinto expression (1) and calculating a processing duration Y. However,the present invention is not limited thus. There may be an example thatsupports fabrication of semiconductor wafers by substituting aprocessing duration Y into expression (1) and calculating a wafer numberX.

In the above exemplary embodiment, an example is described of supportingfabrication of semiconductor wafers. However, the present invention mayalso be applied to supporting processing by predetermined equipment (forexample, tempering machining devices, NC cutting machining devices andthe like) that apply predetermined processing (for example, tempering,cutting or the like) to processing targets other than semiconductorwafers (for example, molded components). In these cases too, processingdurations and numbers of processing targets that can be processed may bepredicted in accordance with predetermined equipment in a similar mannerto the above exemplary embodiment.

According to the second aspect of the present invention, in theprocessing support device according to the first aspect, the firstpredetermined condition may include conditions that the co-ordinatepoint is at a maximum value of the unit count X and the processingduration Y falls in a first duration band.

According to the third aspect of the present invention, in the secondaspect, the first duration band may be processing durations Y, among theprocessing durations Y of co-ordinate points with the maximum value unitcount X represented by the first two-dimensional co-ordinate data, ofwhich positions counting from a minimum processing duration Y areproportions relative to a total number of the co-ordinate points withthe maximum value unit count X of from 5% to 35%.

According to the fourth aspect of the present invention, in the thirdaspect, the proportions may be from 10% to 20%.

According to the fifth aspect of the present invention, in any one ofthe first to the fourth aspects, the second predetermined condition mayinclude a condition that positions counting from a smallest intercept,among intercepts that are objects of judgment of whether or not thesecond predetermined condition is satisfied, are proportions relative toa total number of the judgment object intercepts of from 5% to 35%.

According to the sixth aspect of the present invention, in the fifthaspect, the proportion relative to the total number of intercepts thatare objects of judgment of whether or not the second predeterminedcondition is satisfied may be from 10% to 20%.

According to the seventh aspect of the present invention, in any one ofthe first to the sixth aspects, the predetermined number may be a countof co-ordinate points with values in the top 50%, counting from largerunit count X values, among the co-ordinate points represented by thesecond two-dimensional co-ordinate data.

According to the eighth aspect of the present invention, in any one ofthe first to the eighth aspects, if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data is1,000 or more, the predetermined number may be a number of co-ordinatepoints with values in the top 10%, counting from larger unit count Xvalues, among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data, if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data isbetween 10 and 1,000, the predetermined number is a number ofco-ordinate points with values in the top 50%, counting from larger unitcount X values, among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data, and if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data is 10or less, the predetermined number is the total number.

According to the ninth aspect of the present invention, in the ninthaspect, the third predetermined condition may include a condition that aposition counting from a smallest gradient, among gradients that areobjects of judgment of whether or not the third predetermined conditionis satisfied, is a proportion relative to a total number of the judgmentobject gradients of from 10% to 40%.

According to the tenth aspect of the present invention, in the ninthaspect, the proportion relative to the total number of gradients thatare objects of judgment of whether or not the third predeterminedcondition is satisfied is from 10% to 20%.

According to the eleventh aspect of the present invention, in any one ofthe first to the tenth aspects, the support section may support theprocessing by substituting a unit count X into expression (1), intowhich the intercept b derived by the intercept derivation section andthe gradient a derived by the gradient derivation section aresubstituted, and calculating the processing duration Y.

According to the twelfth aspect of the present invention, in any one ofthe first to eleventh aspects, the co-ordinate points aretwo-dimensional co-ordinate points according to unit counts X andprocessing durations Y indicated by an instructor who instructs theequipment to execute the processing.

According to the fourteenth aspect of the present invention, in thesemiconductor fabrication support device according to the thirteenthaspect, the processing may include processing that conveys thesemiconductors, and the prediction section may predict a time at whichthe semiconductors will arrive at a conveyance destination.

According to the fifteenth aspect of the present invention, in thethirteenth or the fourteenth aspect, the prediction section may predicta processing duration Y using the support section, and the semiconductorfabrication support device may further include a verification sectionthat, using the processing duration Y predicted by the predictionsection, performs at least one of a verification of performance of theequipment and a verification of a duration that is actually required forthe processing.

According to the seventeenth aspect of the present invention, in theprocessing support method according to the sixteenth aspect, the firstpredetermined condition may include conditions that the co-ordinatepoint is at a maximum value of the unit count X and the processingduration Y falls in a first duration band.

According to the eighteenth aspect of the present invention, in theseventeenth aspect, the first duration band may be processing durationsY, among the processing durations Y of co-ordinate points with themaximum value unit count X represented by the first two-dimensionalco-ordinate data, of which positions counting from a minimum processingduration Y are proportions relative to a total number of the co-ordinatepoints with the maximum value unit count X of from 5% to 35%.

According to the nineteenth aspect of the present invention, in theeighteenth aspect, the proportions may be from 10% to 20%.

According to the twentieth aspect of the present invention, in any oneof the seventeenth to the nineteenth aspect, the second predeterminedcondition may include a condition that positions counting from asmallest intercept, among intercepts that are objects of judgment ofwhether or not the second predetermined condition is satisfied, areproportions relative to a total number of the judgment object interceptsof from 5% to 35%.

According to the twenty-first aspect of the present invention, in thetwentieth aspect, the proportion relative to the total number ofintercepts that are objects of judgment of whether or not the secondpredetermined condition is satisfied may be from 10% to 20%.

According to the twenty-second aspect of the present invention, in anyone of the sixteenth to the twenty-first aspects, the predeterminednumber may be a number of co-ordinate points with values in the top 50%,counting from larger unit count X values, among the co-ordinate pointsrepresented by the second two-dimensional co-ordinate data.

According to the twenty-third aspect of the present invention, in anyone of the sixteenth to the twenty-first aspects, if the total number ofco-ordinate points represented by the second two-dimensional co-ordinatedata is 1,000 or more, the predetermined number may be a count ofco-ordinate points with values in the top 10%, counting from larger unitcount X values, among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data, if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data isbetween 10 and 1,000, the predetermined number may be a number ofco-ordinate points with values in the top 50%, counting from larger unitcount X values, among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data, and if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data is 10or less, the predetermined number may be the total number.

According to the twenty-fourth aspect of the present invention, in anyone of the sixteenth to the twenty-third aspects, the thirdpredetermined condition may include a condition that a position countingfrom a smallest gradient, among gradients that are objects of judgmentof whether or not the third predetermined condition is satisfied, may bea proportion relative to a total number of the judgment object gradientsof from 10% to 40%.

According to the twenty-fifth aspect of the present invention, in thetwenty fourth aspect, the proportion relative to the total number ofgradients that are objects of judgment of whether or not the thirdpredetermined condition is satisfied may be from 10% _(t)o 20%.

According to the twenty-sixth aspect of the present invention, in anyone of the sixteenth to the twenty-fifth aspects, the supporting stepmay include supporting the processing by substituting a unit count Xinto expression (1), into which the derived intercept b and the derivedgradient a are substituted, and calculating the processing duration Y.

According to the twenty-seventh aspect of the present invention, in anyone of the sixteenth to the twenty-sixth aspects, the co-ordinate pointsmay be two-dimensional co-ordinate points according to unit counts X andprocessing durations Y indicated by an instructor who instructs theequipment to execute the processing.

According to the twenty-ninth aspect of the present invention, in thesemiconductor fabrication support method according to the twenty-eighthaspect, the processing may include conveyance of the semiconductors, andthe predicting step may include predicting a time at which thesemiconductors will arrive at a conveyance destination.

According to the thirtieth aspect of the present invention, in thesemiconductor fabrication support method according to the twenty-eightor the twenty-ninth aspect, the predicting step may include predicting aprocessing duration Y, by the supporting step, and the semiconductorfabrication support method further includes performing, using theprocessing duration Y predicted by the predicting step, at least one ofa verification of performance of the equipment and a verification of aduration that is actually required for the processing.

What is claimed is:
 1. A processing support device comprising: aprocessor; a memory section that stores first two-dimensionalco-ordinate data that represents processing object unit counts X ofprocessing targets to which predetermined processing is applied bypredetermined equipment and processing durations Y required for theprocessing of the unit counts X of the processing targets as co-ordinatepoints in two dimensions, and second two-dimensional co-ordinate datathat represents unit counts X and processing durations Y for individualtypes of the processing as co-ordinate points in two dimensions; anintercept derivation section that derives, using the processor, anintercept b of a regression equation expressed as the followingexpression (1)Y=aX+b  (1) in which the unit count X is an independent variable, theprocessing duration Y is a dependent variable, and b is an intercept anda is a gradient particular to the equipment, the intercept b being anintercept that satisfies a second condition among intercepts of linesthat pass through a reference co-ordinate point and respectiveco-ordinate points in a region, the reference co-ordinate pointsatisfying a first predetermined condition among the co-ordinate pointsrepresented by the first two-dimensional co-ordinate data stored in thememory section, and the region being bounded by a line that passesthrough the reference co-ordinate point and is parallel to an x-axisrepresenting the unit counts X, a y-axis representing the processingdurations Y and a line that passes through the reference co-ordinatepoint and the origin; a gradient derivation section that derives, usingthe processor, the gradient a, the gradient a being a gradient of a linethat satisfies a third predetermined condition among gradients of linesthat pass through the intercept b derived by the intercept derivationsection and each of all co-ordinate points with a unit count X greaterthan or equal to a predetermined number among the co-ordinate pointsrepresented by the second two-dimensional co-ordinate data stored in thememory section; and a support section that supports, using theprocessor, the processing using expression (1), into which the interceptb derived by the intercept derivation section and the gradient a derivedby the gradient derivation section are substituted, wherein the firstpredetermined condition includes conditions that the co-ordinate pointis at a maximum value of the unit count X and the processing duration Yfalls in a first duration band, and the first duration band isprocessing durations Y, among the processing durations Y of co-ordinatepoints with the maximum value unit count X represented by the firsttwo-dimensional co-ordinate data, of which positions counting from aminimum processing duration Y are proportions relative to a total numberof the co-ordinate points with the maximum value unit count X of from 5%to 35%.
 2. The processing support device according to claim 1, whereinthe proportions are from 10% to 20%.
 3. A processing support devicecomprising: a processor; a memory section that stores firsttwo-dimensional co-ordinate data that represents processing object unitcounts X of processing targets to which predetermined processing isapplied by predetermined equipment and processing durations Y requiredfor the processing of the unit counts X of the processing targets asco-ordinate points in two dimensions, and second two-dimensionalco-ordinate data that represents unit counts X and processing durationsY for individual types of the processing as co-ordinate points in twodimensions; an intercept derivation section that derives, using theprocessor, an intercept b of a regression equation expressed as thefollowing expression (1)Y=aX+b  (1) in which the unit count X is an independent variable, theprocessing duration Y is a dependent variable, and b is an intercept anda is a gradient particular to the equipment, the intercept b being anintercept that satisfies a second condition among intercepts of linesthat pass through a reference co-ordinate point and respectiveco-ordinate points in a region, the reference co-ordinate pointsatisfying a first predetermined condition among the co-ordinate pointsrepresented by the first two-dimensional co-ordinate data stored in thememory section, and the region being bounded by a line that passesthrough the reference co-ordinate point and is parallel to an x-axisrepresenting the unit counts X, a y-axis representing the processingdurations Y and a line that passes through the reference co-ordinatepoint and the origin; a gradient derivation section that derives, usingthe processor, the gradient a, the gradient a being a gradient of a linethat satisfies a third predetermined condition among gradients of linesthat pass through the intercept b derived by the intercept derivationsection and each of all co-ordinate points with a unit count X greaterthan or equal to a predetermined number among the co-ordinate pointsrepresented by the second two-dimensional co-ordinate data stored in thememory section; and a support section that supports, using theprocessor, the processing using expression (1), into which the interceptb derived by the intercept derivation section and the gradient a derivedby the gradient derivation section are substituted, wherein the secondpredetermined condition includes a condition that positions countingfrom a smallest intercept, among intercepts that are objects of judgmentof whether or not the second predetermined condition is satisfied, areproportions relative to a total number of the judgment object interceptsof from 5% to 35%.
 4. The processing support device according to claim3, wherein the proportion relative to the total number of interceptsthat are objects of judgment of whether or not the second predeterminedcondition is satisfied is from 10% to 20%.
 5. The processing supportdevice according to claim 1, wherein the predetermined number is a countof co-ordinate points with values in the top 50%, counting from largerunit count X values, among the co-ordinate points represented by thesecond two-dimensional co-ordinate data.
 6. The processing supportdevice according to claim 5, wherein if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data is1,000 or more, the predetermined number is a number of co-ordinatepoints with values in the top 10%, counting from larger unit count Xvalues, among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data, if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data isbetween 10 and 1,000, the predetermined number is a number ofco-ordinate points with values in the top 50%, counting from larger unitcount X values, among the co-ordinate points represented by the secondtwo-dimensional co-ordinate data, and if the total number of co-ordinatepoints represented by the second two-dimensional co-ordinate data is 10or less, the predetermined number is the total number.
 7. A processingsupport device comprising: a processor; a memory section that storesfirst two-dimensional co-ordinate data that represents processing objectunit counts X of processing targets to which predetermined processing isapplied by predetermined equipment and processing durations Y requiredfor the processing of the unit counts X of the processing targets asco-ordinate points in two dimensions, and second two-dimensionalco-ordinate data that represents unit counts X and processing durationsY for individual types of the processing as co-ordinate points in twodimensions; an intercept derivation section that derives, using theprocessor, an intercept b of a regression equation expressed as thefollowing expression (1)Y=aX+b  (1) in which the unit count X is an independent variable, theprocessing duration Y is a dependent variable, and b is an intercept anda is a gradient particular to the equipment, the intercept b being anintercept that satisfies a second condition among intercepts of linesthat pass through a reference co-ordinate point and respectiveco-ordinate points in a region, the reference co-ordinate pointsatisfying a first predetermined condition among the co-ordinate pointsrepresented by the first two-dimensional co-ordinate data stored in thememory section, and the region being bounded by a line that passesthrough the reference co-ordinate point and is parallel to an x-axisrepresenting the unit counts X, a y-axis representing the processingdurations Y and a line that passes through the reference co-ordinatepoint and the origin; a gradient derivation section that derives, usingthe processor, the gradient a, the gradient a being a gradient of a linethat satisfies a third predetermined condition among gradients of linesthat pass through the intercept b derived by the intercept derivationsection and each of all co-ordinate points with a unit count X greaterthan or equal to a predetermined number among the co-ordinate pointsrepresented by the second two-dimensional co-ordinate data stored in thememory section; and a support section that supports, using theprocessor, the processing using expression (1), into which the interceptb derived by the intercept derivation section and the gradient a derivedby the gradient derivation section are substituted, wherein the thirdpredetermined condition includes a condition that a position countingfrom a smallest gradient, among gradients that are objects of judgmentof whether or not the third predetermined condition is satisfied, is aproportion relative to a total number of the judgment object gradientsof from 10% to 40%.
 8. The processing support device according to claim7, wherein the proportion relative to the total number of gradients thatare objects of judgment of whether or not the third predeterminedcondition is satisfied is from 10% to 20%.
 9. The processing supportdevice according to claim 1, wherein the support section supports, usingthe processor, the processing by substituting a unit count X intoexpression (1), into which the intercept b derived by the interceptderivation section and the gradient a derived by the gradient derivationsection are substituted, and calculating, using the processor, theprocessing duration Y.
 10. The processing support device according toclaim 1, wherein the co-ordinate points are two-dimensional co-ordinatepoints according to unit counts X and processing durations Y indicatedby an instructor who instructs the equipment to execute the processing.11. A semiconductor fabrication support device comprising: a processingsupport device according to claim 1; and a prediction section thatpredicts an end time of processing using the support section, whereinthe processing targets are semiconductors.
 12. The semiconductorfabrication support device according to claim 11, wherein the processingincludes processing that conveys the semiconductors, and the predictionsection predicts a time at which the semiconductors will arrive at aconveyance destination.
 13. The semiconductor fabrication support deviceaccording to claim 11, wherein the prediction section predicts aprocessing duration Y using the support section, and the semiconductorfabrication support device further includes a verification section that,using the processing duration Y predicted by the prediction section,performs at least one of a verification of performance of the equipmentand a verification of a duration that is actually required for theprocessing.
 14. A processing support method comprising: registering, bystoring in a memory section, first two-dimensional co-ordinate data thatrepresents processing object unit counts X of processing targets towhich predetermined processing is applied by predetermined equipment andprocessing durations Y required for the processing of the unit counts Xof the processing targets as co-ordinate points in two dimensions, andsecond two-dimensional co-ordinate data that represents unit counts Xand processing durations Y for individual types of the processing asco-ordinate points in two dimensions; deriving, using a processor, anintercept b of a regression equation expressed as the followingexpression (1)Y=aX+b  (1) in which the unit count X is an independent variable, theprocessing duration Y is a dependent variable, and b is an intercept anda is a gradient particular to the equipment, the intercept b being anintercept that satisfies a second condition among intercepts of linesthat pass through a reference co-ordinate point and respectiveco-ordinates in a region, the reference co-ordinate point satisfying afirst predetermined condition among the co-ordinate points representedby the first two-dimensional co-ordinate data stored in the memorysection, and the region being bounded by a line that passes through thereference co-ordinate point and is parallel to an x-axis representingthe unit counts X, a y-axis representing the processing durations Y anda line that passes through the reference co-ordinate point and theorigin; deriving, using the processor, the gradient a, the gradient abeing a gradient of a line that satisfies a third predeterminedcondition among gradients of lines that pass through the derivedintercept b and each of all co-ordinate points with a unit count Xgreater than or equal to a predetermined number among the co-ordinatepoints represented by the second two-dimensional co-ordinate data storedin the memory section; and supporting, using the processor, theprocessing using expression (1), into which the derived intercept b andthe derived gradient a are substituted, wherein the first predeterminedcondition includes conditions that the co-ordinate point is at a maximumvalue of the unit count X and the processing duration Y falls in a firstduration band, and the first duration band is processing durations Y,among the processing durations Y of co-ordinate points with the maximumvalue unit count X represented by the first two-dimensional co-ordinatedata, of which positions counting from a minimum processing duration Yare proportions relative to a total number of the co-ordinate pointswith the maximum value unit count X of from 5% to 35%.
 15. Asemiconductor fabrication support method comprising: a processingsupport method according to claim 14; and predicting, using theprocessor, an end time of processing, by the supporting step, whereinthe processing targets are semiconductors.
 16. A non-transitory computerreadable medium storing a program causing a computer to execute aprocess for supporting processing, the process comprising: registering,by storing in a memory section, first two-dimensional co-ordinate datathat represents processing object unit counts X of processing targets towhich predetermined processing is applied by predetermined equipment andprocessing durations Y required for the processing of the unit counts Xof the processing targets as co-ordinate points in two dimensions, andsecond two-dimensional co-ordinate data that represents unit counts Xand processing durations Y for individual types of the processing asco-ordinate points in two dimensions; deriving an intercept b of aregression equation expressed as the following expression (1)Y=aX+b  (1) in which the unit count X is an independent variable, theprocessing duration Y is a dependent variable, and b is an intercept anda is a gradient particular to the equipment, the intercept b being anintercept that satisfies a second condition among intercepts of linesthat pass through a reference co-ordinate point and respectiveco-ordinates in a region, the reference co-ordinate point satisfying afirst predetermined condition among the co-ordinate points representedby the first two-dimensional co-ordinate data stored in the memorysection, and the region being bounded by a line that passes through thereference co-ordinate point and is parallel to an x-axis representingthe unit counts X, a y-axis representing the processing durations Y anda line that passes through the reference co-ordinate point and theorigin; deriving the gradient a, the gradient a being a gradient of aline that satisfies a third predetermined condition among gradients oflines that pass through the derived intercept b and each of allco-ordinate points with a unit count X greater than or equal to apredetermined number among the co-ordinate points represented by thesecond two-dimensional co-ordinate data stored in the memory section;and supporting the processing using expression (1), into which thederived intercept b and the derived gradient a are substituted, whereinthe first predetermined condition includes conditions that theco-ordinate point is at a maximum value of the unit count X and theprocessing duration Y falls in a first duration band, and the firstduration band is processing durations Y, among the processing durationsY of co-ordinate points with the maximum value unit count X representedby the first two-dimensional co-ordinate data, of which positionscounting from a minimum processing duration Y are proportions relativeto a total number of the co-ordinate points with the maximum value unitcount X of from 5% to 35%.